The Bot Baseline Fraud in Digital Advertising

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EFFORTS TO INCREASE REACHALSO INCREASE BOTSIn online advertising, reach refers to the number of uniqueindividuals exposed to an ad. When study participantsattempted to increase their reach with run-of-network (RON)campaigns, those campaigns were exposed to higher thanaverage bot fraud, averaging 16 percent.When advertisers demand more traffic, often at the endof the week, month, and quarter, the differential betweenavailable humans and advertiser demand for traffic canbe made up with bots.Bots can make it look easy to reach high volumes of specificaudiences. A bot can look like a sports fan, someone witha six-figure income, someone interested in buying a car,or a grandparent looking for holiday gifts for grandchildren.White Ops has historically observed that campaigns aroundtime-sensitive releases such as retail sales, movies, and TVshows are unusually vulnerable to bot activity because theyhave very specific delivery windows that can exacerbate thebot problem.CASE STUDYBots Spiked Every SaturdayFor one beer/spirits participant,a bot spike occurred at the end ofevery week of a campaign, with botsspiking at noon (PST) on Saturday,uniformly increasing from zero to800 bots per hour before droppingback to zero bots per hour after thepeak at noon on Saturday.Bot levels dropped to nearly zerofor all other days of the week (shownin the nearly empty columns of thegraph, at right). The bot spikes onSaturdays comprised 95 percent ofall the bot fraud for this campaign.BOTS DETECTED PER HOUR8006004002000AUG. SEPT. OCT.Each dot placed on the y-axis representsthe number of bots detected during eachhour of the study.DAILY CAMPAIGN BOT LEVELSFigure 3: Bots Spiked in This Campaign Every Saturday at 12 P.M.14
BOT TRAFFIC VARIES BY DOMAIN CATEGORYNo consistent variation in bot traffic percentage was evident across participant industry verticals.However, when we correlated our bot results with domain content analysis from Grapeshot, bottraffic varied notably across domain categories where the ads were served.Finance22%Family18%Food16%Travel11%Health10%Home10%DOMAIN CATEGORYEconomyFashionSocietyEducationEntertainmentBusiness 4%7%7%6%6%9%Finance, family, and food domainshad the highest percentages ofbots, with 16–22 percent bots.Tech, sport, and science had thelowest bot percentages, rangingfrom 3–4 percent bots.Politics4%News4%Tech4%Sport3%Science3%Info2%0 5 10 15 20 25BOT PERCENTAGEFigure 4: Finance, Family, and Food Domains Had Higher Bot PercentagesDomain category data was provided by Grapeshot.15
Page 1 and 2: The Bot Baseline:Fraud in DigitalAd
Page 3 and 4: Special Thanks to the FollowingANA
Page 5 and 6: ABOUT THE STUDY
Page 7 and 8: BOTS ARE EVERYWHERE...BUT NOT IN EQ
Page 9 and 10: HOW WE USED THE DATAThis study is a
Page 11 and 12: BOTS WERE IN EVERY KINDOF CAMPAIGN
Page 13: BOT FRAUD VARIES OVER TIMENot all b
Page 17 and 18: SOURCING TRAFFIC INCREASESBOT LEVEL
Page 19 and 20: BOTS GET INTO PREMIUM BUYSSignifica
Page 21 and 22: TO REDUCE BOTS IN PREMIUM CAMPAIGNS
Page 23 and 24: BOTS ARE BUILT TO FOOL ALL STAKEHOL
Page 25 and 26: ADWARE: NOT ALL ATTACKS ARE THE SAM
Page 27 and 28: BOTNET CONTROLLERS HIJACK EVERYDAYU
Page 29 and 30: BOTS FAKED ALL OF THE ENGAGEMENT AN
Page 31 and 32: BOTS ARE GETTING TARGETED AND RETAR
Page 33 and 34: HOW BOTSUPPLIERS GETAWAY WITH IT:EV
Page 35 and 36: BOT SUPPLIERS ACTIVELY DISGUISE BOT
Page 37 and 38: SITES THAT ONLYA BOT COULDLOVE37
Page 39 and 40: BOT SUPPLIERS ARE WATCHING YOUBot t
Page 41 and 42: WHEN PUBLISHERSARE VICTIMS TOO:AD I
Page 43 and 44: AD INJECTIONDEGRADES THEQUALITY OFT
Page 45 and 46: BOTNET OPERATORS ARE ALREADYDEFEATI
Page 47 and 48: Action Plan for All StakeholdersCre
Page 49 and 50: Action Plan for Buyers(Continued)Ap
Page 51 and 52: Who is your real audience:BOB SMITH
Page 53 and 54: Appendix AGlossary of Terms (Contin
Page 55 and 56: Appendix BConstraints and Limitatio
Page 57: Appendix DIllustrative Terms and Co

The Bot Baseline Fraud in Digital Advertising

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